Negotiating space: The daily mobility of women waste pickers in Cuenca, Ecuador
Bibliographic record
Abstract
In many cities across Latin America, Africa, and South Asia, informal women waste pickers play a crucial role in managing recyclable waste, reducing municipal costs and urban carbon footprints. Despite their contributions, limited attention to their mobility patterns reflects the low priority governments, academia and society assign to understanding their particular needs, hindering the development of inclusive policies and innovative methodologies. This study introduces a mixed methods approach to study the spatial behavior of informal urban waste pickers. The methodology comprises three stages: First, a survey and mapping techniques, reveal the spatial distribution of residence, work and storage locations, mode of transport, and collection tools. Second, GPS tracking identifies mobility patterns, dominant flows and clusters of their collection routes. Third, multi-sited ethnography uncovers the reasons and perceptions behind their daily movements. The integration of these three stages highlights the factors that constrain and limit their mobility. Applied in Cuenca, Ecuador, this method establishes a baseline for understanding women waste pickers' spatial behavior. Results show that waste pickers walk up to 16 km daily, navigating spatial, economic, physical, and social challenges. By focusing on women's everyday lives, this study reveals socio-spatial inequalities and provides a robust foundation for advocating effective, inclusive public policies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".